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###移植yolo2到caffe框架过程中用到的一些关键文件   0. yolo-in-caffe源码

  1. yolo.prototxt   yolo2的网络配置文件,对应着darknet中的yolo.cfg编写
  2. conver_weights_to_caffemodel.py
    将yolo2的weights文件转化为caffemodel文件
    可能需要更改prototxt和weights的路径
  3. compare_output.py
    比较darknet和caffe各层输出的脚本文件,使用这个脚本比较是一种可靠的方式,但是也可以把数据图形化显示,这样更容易比较,而且不用在意数值上的严格相等
    python compare_output.py layer_output_in_caffe layer_output_in_darknet
  4. save_sized_image.py
    在caffe框架中保存resize后的图片到sized_image.npy 仍然有一个问题,caffe保存的sized_image.npg 和 darknet中保存的sized_image 两个进行数据比对时并不完全一致,我使用compare_output.py 比对两个数据时,发现在一定误差范围内,数据的相似性(暂且叫这个)大概在90%多,这样应该不会影响到后边图像的特征提取
  5. 效果展示

    image

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